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Magnetic Normal Modes of Bi-Component Permalloy Structures Declarative Variables in Online Dating: a Mixed-Method Analysis of a Mimetic-Distinctive Mechanism JESSICA PIDOUX, Digital Humanities Institute, EPFL, Switzerland PASCALE KUNTZ, Laboratoire des Sciences du Numérique de Nantes, University of Nantes, France DANIEL GATICA-PEREZ, Idiap Research Institute and EPFL, Switzerland Declarative 1 variables of self-description have a long-standing tradition in matchmaking media. With the advent of online dating platforms and their brand positioning, the volume and semantics of variables vary greatly across apps. However, a variable landscape across multiple platforms, providing an in-depth understanding of the dating structure offered to users, has hitherto been absent in the literature. In this study, more than 300 declarative variables from 22 Anglophone and Francophone dating apps are examined. A mixed-method research design is used, combining hierarchical classification with an interview analysis of nine founders and developers in the industry. We present a new typology of variables in nine categories and a classification of dating apps, which highlights a double mimetic-distinctive mechanism in the variable definition and reflects the dating market. From the interviews, we extract three main factors concerning the economic and sociotechnical framework of coding practices, the actors’ personal experience, and the development methodologies including user traces that influence this mechanism. This work, which to our knowledge is the most extensive thus far on dating app declarative variables, provides a new perspective on the analysis of the intersection between developers and users of online dating, which is mediated through variables, among other components. CCS Concepts: • Human-centered computing~Human computer interaction (HCI)~Empirical studies in HCI; • Human-centered computing~Human computer interaction (HCI)~HCI design and evaluation methods~User models; • Human-centered computing~Human computer interaction (HCI)~Interaction paradigms~Graphical user interfaces; • Human-centered computing~Collaborative and social computing~Collaborative and social computing theory, concepts and paradigms~Social engineering (social sciences) KEYWORDS: Declarative variables, user representation, matching systems, online dating, mixed-method ACM Reference format: Jessica Pidoux, Pascale Kuntz and Daniel Gatica-Perez. 2021. Declarative Variables in Online Dating: a Mixed-Method Analysis of a Mimetic-Distinctive Mechanism. In Proceedings of the ACM on Human-Computer Interaction, Vol. 5, CSCW1, Article 100 (April 2021), 30 pages, https://doi.org/10.1145/3449174. 1Author’s addresses: J. Pidoux. Digital Humanities Institute, École Polytechnique Fédérale de Lausanne, CDH-DHI, Station 14, CH-1015 Lausanne, Switzerland, P. Kuntz, Laboratoire des Sciences du Numérique de Nantes, Polytech Nantes, 44 300 Nantes cedex, France, D. Gatica-Perez, Idiap Research Institute, CH-1920 Martigny, Switzerland, and École Polytechnique Fédérale de Lausanne, STI-IEL and CDH-DHI, CH-1015 Lausanne, Switzerland. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. 2573-0142/2021/April – Article100 $15.00 Copyright is held by the owner/author(s). Publication rights licensed to ACM. https://doi.org/10.1145/3449174 PACM on Human-Computer Interaction, Vol. 5, No. CSCW1, Article 100, Publication date: April 2021. 100:2 Jessica Pidoux et al. 1 INTRODUCTION Benjamin Franklin suggested applying Moral Algebra to his nephew’s decision to choose a wife in 1779. This consists in creating a balanced list of two columns (pros and cons) on a sheet of paper with attributed motives and weights [34]. The method was adapted half a century later by Charles Darwin for his cousin [49], where one can observe a sequence of items and short sentences, organized horizontally in lines, thus introducing the “table, as a graphical reduction structuring and ordering knowledge” [35]. Variables such as age, profession, education and traits of character, in more or less structured lists [1], have long served matchmaking purposes. From personal ads in the press to machine-readable paper questionnaires in matrimonial bureaus, these media can be traced back to their 18th-century usage by private individuals and intermediary experts such as marriage brokers [23]. Thereinafter, Minitel France in the 1980s (with its “pink” messaging service) and Bulletin Board Systems in the USA [8] influenced computer-mediated dating through new practices of “technical writing” via graphical interfaces [11]. Today, datafication of dating from mobile apps and websites involves large sets of variables stored in databases, which are interoperable across platforms, for matching, profiling and targeting advertisements [4]. Roughly speaking, these variables can be classified into two categories: (i) the “invisible” variables allowing the collection of data without the user’s knowledge, and (ii) the “declarative” variables directly accessible from the GUI, which are presented to users through dedicated profile sections and questionnaires for self- description and defining the target profiles. Both types allow for the collection of user behaviour from both the dating platforms and from exogenous sources, such as social media. Together they feed the input variable set of the algorithms, but only the latter type is directly available to academic scientists (due to intellectual property rights) and can be collected without affecting user privacy. The declarative variables, which are completed during the often-mandatory registration step [81], are the prime mediation between users and the system, and they play an active role in various interactions from online dating to face-to-face meetings. The human-computer interaction and social computing literature, completed by works disseminated in different research communities, reflects a large variety of uses: filtering user research preferences on the interface [38], self- description [80,81] and representation according to an ideal audience [17], safe self-disclosure [30], attractiveness assessment [32], increasing trust [33,71], and as benchmarks for finding new strategies to overcome the constraints of self-presentation and evaluation within the platform [29]. Variables are defined according to the economic logic of dating [2] and are a valuable means for improving user preference learning in computing matching proposals. In addition, the role of declarative variables is extended to in-person meetings in order to start a conversation [48] and to validate the other person’s offline identity by comparing it with the profile [47]. Consequently, variables contribute to shaping both user experiences and algorithm search spaces. These are a key component of the collective knowledge that is created by both the users that feed platform databases via input values and by the developers that define them. However, in the computing literature, variables are often considered as abstract components, and the rationale for their inclusion in a profile are most often unknown to users (e.g., [77,78]). In the human-computer interaction and social computing literature, the variable role for users has been studied extensively but, to our knowledge, their implications for the mediation process between the dating app developers and the users have rarely been explored [8,22]. Our paper thus investigates the declarative variables used in these platforms to shed light on user profiles crafted in the dating industry, as an entry point, albeit partial, to proprietary algorithms influencing mate choice preferences. In addition, it elucidates a few mechanisms associated with the practices of the dating app founders and developers that guide the variable construction. Specifically, using a combination of exploratory PACM on Human-Computer Interaction, Vol. 5, No. CSCW1, Article 100, Publication date: April 2021. Declarative Variables in Online Dating: a Mixed-Method Analysis of a Mimetic-Distinctive Mechanism 100:3 data analysis and a qualitative approach based on interviews, we address the two following research questions: RQ1: Given the declarative variables collected from a set of dating apps, which main variable arrangements structure the dating profiles in direct mediation with users? RQ2: Following dating app founders' and developers’ personal and professional experiences, which factors influence the definition of declarative variables shaping user modeling and matching? To address these questions, we follow a mixed-method research design, which goes beyond the previous analyses based on either qualitative or quantitative data. We manually extracted and built a dataset of 317 declarative variables from 22 online dating Anglophone and Francophone platforms, subsequent to registration and profile creation in each platform as a user. Moreover, we interviewed nine developers and founders involved in the conceptual design of ten dating apps. Our paper includes the following contributions: (1) To address RQ1, we computed two classifications: one
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